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https://github.com/vale981/ray
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258 lines
9.5 KiB
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258 lines
9.5 KiB
ReStructuredText
Installing Ray
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==============
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.. tip:: Join our `community slack <https://forms.gle/9TSdDYUgxYs8SA9e8>`_ to discuss Ray!
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Ray currently supports MacOS and Linux.
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Windows wheels are now available, but :ref:`Windows support <windows-support>` is experimental and under development.
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Latest stable version
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---------------------
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You can install the latest stable version of Ray as follows.
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.. code-block:: bash
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pip install -U ray # also recommended: ray[debug]
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**Note for Windows Users:** To use Ray on Windows, Visual C++ runtime must be installed (see :ref:`Windows Dependencies <windows-dependencies>` section). If you run into any issues, please see the :ref:`Windows Support <windows-support>` section.
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.. _install-nightlies:
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Latest Snapshots (Nightlies)
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----------------------------
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Here are links to the latest wheels (which are built for each commit on the
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master branch). To install these wheels, use the following ``pip`` command and wheels
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instead of the ones above:
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.. code-block:: bash
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pip install -U [link to wheel]
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=================== =================== ======================
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Linux MacOS Windows (experimental)
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=================== =================== ======================
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`Linux Python 3.8`_ `MacOS Python 3.8`_ `Windows Python 3.8`_
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`Linux Python 3.7`_ `MacOS Python 3.7`_ `Windows Python 3.7`_
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`Linux Python 3.6`_ `MacOS Python 3.6`_ `Windows Python 3.6`_
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`Linux Python 3.5`_ `MacOS Python 3.5`_
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=================== =================== ======================
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.. _`Linux Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp38-cp38-manylinux1_x86_64.whl
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.. _`Linux Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp37-cp37m-manylinux1_x86_64.whl
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.. _`Linux Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp36-cp36m-manylinux1_x86_64.whl
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.. _`Linux Python 3.5`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp35-cp35m-manylinux1_x86_64.whl
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.. _`MacOS Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp38-cp38-macosx_10_13_x86_64.whl
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.. _`MacOS Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp37-cp37m-macosx_10_13_intel.whl
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.. _`MacOS Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp36-cp36m-macosx_10_13_intel.whl
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.. _`MacOS Python 3.5`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp35-cp35m-macosx_10_13_intel.whl
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.. _`Windows Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp38-cp38-win_amd64.whl
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.. _`Windows Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp37-cp37m-win_amd64.whl
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.. _`Windows Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp36-cp36m-win_amd64.whl
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Installing from a specific commit
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---------------------------------
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You can install the Ray wheels of any particular commit on ``master`` with the following template. You need to specify the commit hash, Ray version, Operating System, and Python version:
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.. code-block:: bash
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pip install https://ray-wheels.s3-us-west-2.amazonaws.com/master/{COMMIT_HASH}/ray-{RAY_VERSION}-{PYTHON_VERSION}-{PYTHON_VERSION}m-{OS_VERSION}_intel.whl
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For example, here are the Ray 0.9.0.dev0 wheels for Python 3.5, MacOS for commit ``a0ba4499ac645c9d3e82e68f3a281e48ad57f873``:
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.. code-block:: bash
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pip install https://ray-wheels.s3-us-west-2.amazonaws.com/master/a0ba4499ac645c9d3e82e68f3a281e48ad57f873/ray-0.9.0.dev0-cp35-cp35m-macosx_10_13_intel.whl
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Installing Dashboard
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--------------------
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The dashboard requires a few additional Python packages, which can be installed
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via pip.
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.. code-block:: bash
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pip install ray[dashboard]
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The command ``ray.init()`` or ``ray start --head`` will print out the address of
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the dashboard. For example,
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.. code-block:: python
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>>> import ray
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>>> ray.init()
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======================================================================
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View the dashboard at http://127.0.0.1:8265.
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Note: If Ray is running on a remote node, you will need to set up an
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SSH tunnel with local port forwarding in order to access the dashboard
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in your browser, e.g. by running 'ssh -L 8265:127.0.0.1:8265
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<username>@<host>'. Alternatively, you can set dashboard_host="0.0.0.0" in
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the call to ray.init() to allow direct access from external machines.
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======================================================================
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.. _windows-support:
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Windows Support
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---------------
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Windows support is currently limited and "alpha" quality.
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Bugs, process/resource leaks, or other incompatibilities may exist under various scenarios.
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Unusual, unattended, or production usage is **not** recommended.
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To use Ray on Windows, the Visual C++ runtime must be installed (see :ref:`Windows Dependencies <windows-dependencies>` section).
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If you encounter any issues, please try the following:
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- Check the `Windows Known Issues <https://github.com/ray-project/ray/issues/9114>`_ page on GitHub to see the latest updates on Windows support.
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- In the case that your issue has been addressed, try installing the :ref:`latest nightly wheels <install-nightlies>`.
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If your issue has not yet been addressed, comment on the `Windows Known Issues <https://github.com/ray-project/ray/issues/9114>`_ page.
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.. _windows-dependencies:
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Windows Dependencies
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~~~~~~~~~~~~~~~~~~~~
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For Windows, ensure the latest `Visual C++ runtime`_ (`install link`_) is installed before using Ray.
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Otherwise, you may receive an error similar to the following when Ray fails to find
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the runtime library files (e.g. ``VCRUNTIME140_1.dll``):
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.. code-block:: bash
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FileNotFoundError: Could not find module '_raylet.pyd' (or one of its dependencies).
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.. _`Visual C++ Runtime`: https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads
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.. _`install link`: https://aka.ms/vs/16/release/vc_redist.x64.exe
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Installing Ray on Arch Linux
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----------------------------
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Note: Installing Ray on Arch Linux is not tested by the Project Ray developers.
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Ray is available on Arch Linux via the Arch User Repository (`AUR`_) as
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``python-ray``.
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You can manually install the package by following the instructions on the
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`Arch Wiki`_ or use an `AUR helper`_ like `yay`_ (recommended for ease of install)
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as follows:
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.. code-block:: bash
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yay -S python-ray
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To discuss any issues related to this package refer to the comments section
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on the AUR page of ``python-ray`` `here`_.
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.. _`AUR`: https://wiki.archlinux.org/index.php/Arch_User_Repository
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.. _`Arch Wiki`: https://wiki.archlinux.org/index.php/Arch_User_Repository#Installing_packages
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.. _`AUR helper`: https://wiki.archlinux.org/index.php/Arch_User_Repository#Installing_packages
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.. _`yay`: https://aur.archlinux.org/packages/yay
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.. _`here`: https://aur.archlinux.org/packages/python-ray
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Installing Ray with Anaconda
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----------------------------
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If you use `Anaconda`_ and want to use Ray in a defined environment, e.g, ``ray``, use these commands:
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.. code-block:: bash
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conda create --name ray
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conda activate ray
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conda install --name ray pip
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pip install ray
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Use ``pip list`` to confirm that ``ray`` is installed.
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.. _`Anaconda`: https://www.anaconda.com/
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Building Ray from Source
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------------------------
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Installing from ``pip`` should be sufficient for most Ray users.
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However, should you need to build from source, follow :ref:`these instructions for building <building-ray>` Ray.
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Docker Source Images
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--------------------
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Run the script to create Docker images.
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.. code-block:: bash
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cd ray
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./build-docker.sh
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This script creates several Docker images:
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- The ``ray-project/deploy`` image is a self-contained copy of code and binaries
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suitable for end users.
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- The ``ray-project/examples`` adds additional libraries for running examples.
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- The ``ray-project/base-deps`` image builds from Ubuntu Xenial and includes
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Anaconda and other basic dependencies and can serve as a starting point for
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developers.
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Review images by listing them:
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.. code-block:: bash
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docker images
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Output should look something like the following:
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.. code-block:: bash
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REPOSITORY TAG IMAGE ID CREATED SIZE
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ray-project/examples latest 7584bde65894 4 days ago 3.257 GB
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ray-project/deploy latest 970966166c71 4 days ago 2.899 GB
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ray-project/base-deps latest f45d66963151 4 days ago 2.649 GB
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ubuntu xenial f49eec89601e 3 weeks ago 129.5 MB
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Launch Ray in Docker
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~~~~~~~~~~~~~~~~~~~~
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Start out by launching the deployment container.
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.. code-block:: bash
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docker run --shm-size=<shm-size> -t -i ray-project/deploy
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Replace ``<shm-size>`` with a limit appropriate for your system, for example
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``512M`` or ``2G``. The ``-t`` and ``-i`` options here are required to support
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interactive use of the container.
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**Note:** Ray requires a **large** amount of shared memory because each object
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store keeps all of its objects in shared memory, so the amount of shared memory
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will limit the size of the object store.
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You should now see a prompt that looks something like:
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.. code-block:: bash
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root@ebc78f68d100:/ray#
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Test if the installation succeeded
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To test if the installation was successful, try running some tests. This assumes
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that you've cloned the git repository.
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.. code-block:: bash
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python -m pytest -v python/ray/tests/test_mini.py
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